The growing extent and variety of present military operations forces to use the resources in hand at its best. Especially, the optimum usage and assignment of limited number of the air force resources to missions will provide a considerable advantage in the battle field. The problem of finding the feasible and optimum assignment has been known to be studied / yet performing the process faster is still a topic that captures researchers&rsquo / attention because of the computational complexity that the assignment problem involves within.
In this thesis, exploring the optimal assignment of fleets/aircrafts to targets/groups of targets is going to be performed via algorithms and heuristics. As the best choice for finding the exact solution, Branch-and-Bound algorithm, which is an intelligent way of searching for the solution on a solution tree where the nodes with potential of not leading to the solution are fathomed, has been investigated and applied according to the specific problem needs. The number of nodes on the search tree increases exponentially as the problem size increases. Moreover / as the size of the assignment problem increases, attaining the solution solely by Branch-and-Bound algorithm is definitely computationally expensive due to memory and time requirements. Therefore, Genetic algorithm which can provide good solutions in a relatively short time without having computational difficulties is considered as the second algorithm. Branch-and-Bound algorithm and Genetic algorithm are separately used for obtaining the solution. Hybrid algorithms which are combinations of Branch-and-Bound and Genetic algorithms are used with heuristics for improving the results.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/3/12610154/index.pdf |
| Date | 01 December 2008 |
| Creators | Rizvanoglu, Emre |
| Contributors | Leblebicioglu, Kemal |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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